US7174232B2 - Job release with multiple constraints - Google Patents
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- US7174232B2 US7174232B2 US10/979,069 US97906904A US7174232B2 US 7174232 B2 US7174232 B2 US 7174232B2 US 97906904 A US97906904 A US 97906904A US 7174232 B2 US7174232 B2 US 7174232B2
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32258—Resource, machine assignment preferences, actual and anticipated load
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32269—Decision, of job release, select job to be launched next in shop
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32309—Shortest remaining capacity
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/80—Management or planning
Definitions
- the present invention generally relates to the release of jobs, as in a production environment. More particularly, the invention relates to the release of jobs based on the application of multiple constraints.
- a job is a number of items to be processed, or a number of tasks to be completed. Processing of an item may for example comprise building or assembling a product, or a part of a product, from raw materials or components.
- the terms “items”, “products” and “parts” may be used interchangeably to refer to units to be processed.
- a job may be governed by a “work order” which describes the set of operations to be performed to process a specified number of units of a particular item (or group of items) or the set of operations to be performed to complete a particular task. In certain production environments (e.g. in the semiconductor field), jobs may be referred to as “lots”.
- Jobs have various attributes, such as a desired quantity of units, item characteristics, release date, due date, and the like, which may vary from job to job. Although many jobs be associated with a single type of item (e.g. a particular product), some jobs may be associated with two or more different types of items having similar characteristics. For example, in the semiconductor industry, items may be grouped into jobs based on product attributes, such as package type, lead count, pad size, device type and the associated motherlot, waferlot, and sublot identifiers.
- product attributes such as package type, lead count, pad size, device type and the associated motherlot, waferlot, and sublot identifiers.
- Machines may be grouped into work centers.
- a “work center” is a set of one or more machines having similar capabilities, each machine being capable of performing the same general processing operation.
- a “Wire Bond” work center may contain multiple wire bonders which come from different equipment manufacturers, yet they are all generally capable of completing the wire bonding operation.
- the terms “work center” and “operation” are sometimes used interchangeably.
- Job release is an important and critical step in production planning.
- job release refers to the release of jobs from a pool of pending jobs for processing by machines on the shop floor.
- Job release scheduling dictates which jobs are to be released to the shop floor, at what time, and in what quantity of units (i.e. whether the job will be fully released or partially released).
- a job is said to be fully or 100% released to the shop floor when processing of all of the units comprising the job has been designated to commence during a particular time interval.
- a job is said to be partially released when processing of only some of the units comprising the job has been designated to commence during a particular time interval.
- a distinction should be made between the release of a job i.e.
- a job may be fully or partially released even though no processing of the job has yet commenced.
- X % released When a job is partially released, it may be deemed to be “X % released”, where X is a percentage determined from the ratio of the number of units that have been released over the total number of desired units in the job.
- Job dispatching refers to the scheduling of released jobs already on the production floor. Released jobs could be yet to be processed, i.e. queued at the first work center; currently being processed at a work center; or currently queued at an intermediate work center. In conventional production planning, job release and job dispatching are planned separately. It is said that job release control plays a more significant role than job dispatching in effective shop floor scheduling.
- WIP Work-in-Process
- WIP generally refers to a product or products in various stages of completion throughout a processing facility, including raw material that has been released for initial processing through to completely processed products awaiting final inspection.
- the Bottleneck strategy attempts to maintain an appropriate work load at a bottleneck operation.
- a bottleneck operation is an operation having limited processing capacity which may restrict the number of units of an item that can be processed during a time interval.
- the Global input/output strategy attempts to maintain a zero differential between the number of jobs released and completed over a given time interval.
- the Fixed Quantity Release strategy attempts to achieve a desired production output target.
- Setup time is the time required for a specific machine, resource, work center, or production line to convert from the production of the last good piece of an earlier released lot to the first good piece of a later released lot.
- machine information and information about items to be processed are used to determine available machine capacity. Available machine capacity is allocated to jobs subject to multiple job release constraints. Allocation may be performed first for any pending jobs which were partially released during a previous time interval, and then to new jobs in decreasing order of determined job rank. If different operative constraints dictate different numbers of units of a job to be released, the minimum number of units meeting each constraint may be released. After the number of units to be released has been determined for a job, machine information is updated to account for available capacity consumed by the release of the selected number of units of the job. Updated information may be used for job release scheduling of the next job.
- the job release constraints may include any of (1) a baseline capacity constraint; (2) a bottleneck capacity constraint; (3) a machine preference constraint; (4) a fixture/tooling capacity constraint (if the machine preference constraint is also operative); (5) WIP balancing constraint; (6) a committed forecast constraint; and (7) a loading pattern constraint.
- a method of scheduling the release of jobs from a pool of pending jobs comprising: selecting a job; determining available machine capacity for the job based on job characteristics of the job and machine information including machine availability information about one or more machines capable of processing the job; allocating at least some of the available machine capacity to the job subject to multiple job release constraints; and updating the machine availability information to reflect the allocating.
- a machine-readable medium including code for scheduling the release of jobs from a pool of pending jobs, comprising: machine-executable code for selecting a job; machine-executable code for determining available machine capacity for the job based on job characteristics of the job and machine information including machine availability information about one or more machines capable of processing the job; machine-executable code for allocating at least some of the available machine capacity to the job subject to multiple job release constraints; and machine-executable code for updating the machine availability information to reflect the allocating.
- a computing device comprising a processor and persistent storage memory in communication with the processor storing machine-readable code for directing the device to schedule the release of jobs from a pool of pending jobs, comprising: means for selecting a job; means for determining available machine capacity for the job based on job characteristics of the job and machine information including machine availability information about one or more machines capable of processing the job; means for allocating at least some of the available machine capacity to the job subject to multiple job release constraints; and means for updating the machine availability information to reflect the allocating.
- FIG. 1 illustrates a production facility having machines in respect of which job release is being determined
- FIG. 2 illustrates an exemplary job release system and its various inputs and outputs
- FIG. 3 illustrates a machine time line indicative of machine availability for an exemplary machine
- FIG. 4 illustrates an exemplary set of machine processing rate information for one of the work centers illustrated in FIG. 1 ;
- FIG. 5 illustrates an exemplary set of machine preference levels for one of the work centers illustrated in FIG. 1 ;
- FIG. 6 illustrates high-level operation for performing job release scheduling for a pool of pending jobs
- FIG. 7 illustrates the initialization operation of FIG. 6 in greater detail
- FIGS. 8A and 8B illustrate the ranking of a set of new jobs using primary and secondary job ranking criteria respectively
- FIG. 9 illustrates job release scheduling in greater detail
- FIG. 10 illustrates an exemplary baseline capacity constraint definition which may be used to specify one or more baseline capacity job release constraints
- FIG. 11 illustrates the job characteristics of an exemplary job in respect of which the baseline capacity constraint definition of FIG. 10 may be applied;
- FIG. 12 illustrates job release scheduling performed with a machine preference job release constraint having been activated
- FIG. 13 illustrates an exemplary fixture capacity definition which may be used to specify one or more fixture job release capacity constraints
- FIG. 14 illustrates an exemplary fixture usage matrix which may be employed when a fixture job release capacity constraint is activated
- FIG. 15 illustrates the specification of various degrees of required similarity between characteristics of jobs in adjacent time intervals for an operative loading pattern job release constraint
- FIGS. 16A , 16 B, 16 C and 16 D illustrate the definition of patterns of job characteristics for purposes of identifying different degrees of similarity between jobs in adjacent time intervals
- FIG. 17 illustrates an alternative representation of the operation illustrated in FIGS. 6 , 7 and 9 ;
- FIGS. 18A to 18E illustrate forecast processing start dates and finished goods dates as determined by an alternative embodiment of the job release system
- FIG. 19 illustrates available-to-promise quantities for an item of interest as determined by an alternative embodiment of the of the job release system
- FIG. 20 illustrates a time line indicating some of the available-to-promise quantities set forth in FIG. 19 ;
- FIG. 21 illustrates various available-to-promise quantities as determined by the alternative embodiment of FIG. 19 prior to specification of an ad hoc quantity for a prospective spot order
- FIG. 22 illustrates the available-to-promise quantities of FIG. 21 after specification of an ad hoc quantity for a prospective spot order.
- a production facility 100 having two work centers 110 and 120 is shown.
- Each work center 110 and 120 is a set of machines having similar capabilities at which a particular job processing operation can be performed.
- the operation that a work center is capable of completing is referred to herein using the same reference numeral as is used for the work center.
- work center 110 has five machines MC 001 , MC 002 , MC 003 , MC 004 and MC 005 , each capable of performing operation 110
- work center 120 has two machines MC 701 and MC 702 , each capable of performing operation 120 .
- the machines of work center 110 are further subdivided into two machine groups 112 and 114 .
- a machine group is a grouping of machines within a work center which are of the same model and/or have the same manufacturer. Machines within a machine group generally have the same or similar characteristics (e.g. the same processing rate for a particular item).
- FIG. 2 illustrates an exemplary job release system 200 (or job release “engine” 200 ) and its various inputs and outputs.
- the job release system 200 is responsible for scheduling the release of jobs from a pool of pending jobs to the shop floor (i.e. to production facility 100 ) based on multiple operative job release constraints selected by a user.
- Job release system 200 may comprise a computing device such as a PC having a processor, persistent storage memory storing an operating system such as Microsoft® WindowsTM XP, a display, and an input device such as a keyboard and/or mouse (not shown), executing machine-executable code loaded into the system 200 from a machine-readable medium 230 , which could be a magnetic or optical disk, a tape, a chip, or another form of primary or secondary storage for example.
- a machine-readable medium 230 which could be a magnetic or optical disk, a tape, a chip, or another form of primary or secondary storage for example.
- the job release system 200 may be referred to as a “lot release system (or engine) 200 ”. If the term “lot” is used herein, it should be understood to more generally refer to a “job”.
- inputs to the job release system 200 include a set of job release constraints 202 , machine information 204 , a pool of pending jobs 206 , a master production schedule (MPS) 208 , a set user-specified job ranking criteria 210 to be applied to new jobs, and a WIP status 212 .
- MPS master production schedule
- Job release constraints 202 are a set of one or more operative constraints which govern the job release scheduling performed the job release system 200 .
- the operative constraints are selected by a user of the system 200 , e.g., through interaction with a graphical user interface presented on a display of the system 200 .
- each operative constraint should be satisfied to the maximum possible extent in order for a job to be released.
- seven selectively-engageable constraints are available. These include a baseline capacity constraint, a bottleneck capacity constraint, a machine preference constraint, a fixture/tooling capacity constraint, a WIP balancing constraint, a committed forecast constraint, and a loading pattern constraint.
- These constraints are each capable of being independently “toggled”, with some exceptions that will become apparent. Each of these constraints is described in greater detail below.
- Machine information 204 (which may alternatively be referred to as the “common factory model”) includes various types of information about the production facility 100 ( FIG. 1 ) in respect of which job release scheduling is to be performed.
- Machine information 204 includes information identifying the number and type of machines in production facility 100 and their grouping into work centers 110 , 120 .
- Machine information 204 also includes machine availability information and machine processing rate information.
- Machine availability information indicates, for each machine shown in FIG. 1 , the availability of the machine for processing jobs during a time interval of interest.
- Machine availability information may be represented in various ways. For example, one or more time lines may be maintained for each machine to reflect machine availability and allocation status. The time lines may identify time slots during which the machine is already booked for processing a job, time slots during which the machine is unavailable for other reasons (e.g. scheduled for preventative maintenance, meal break, or holiday shutdown), and time slots during which the machine is available. For each machine, timelines of various levels of granularity may be provided.
- a first time line may indicate the availability of a machine on a week-to-week basis for a given production year
- a second time line may indicate the availability of the machine on a day-to-day basis for a given week of interest (e.g. week 6 of the production year)
- a third time line may indicate the hour-to-hour availability of the machine during a particular shift on a current day from week 6.
- Timelines may be represented in software in various ways (e.g. as linked lists or matrices for example).
- An exemplary machine time line 300 is illustrated in FIG. 3 .
- Machine processing rate information indicates the rate at which each of the machines of FIG. 1 is capable of processing jobs in the pool of pending jobs 206 .
- processing rates are expressed in terms of a rate (units per hour) at which the machines of FIG. 1 are capable of processing the items with which the jobs in pool 206 are associated.
- machine processing rate information is used in order to convert a machine's available time into a corresponding number of units of a particular item which can be processed during that available time, for purposes of determining how many units of a particular job can be released during the time interval of interest.
- An exemplary set of machine processing rate information 400 for the machines of work center 120 is illustrated in FIG. 4 .
- machine information 204 may additionally include machine preference information indicating, for each machine in the production facility 100 , the preference (or suitability) of that machine for processing each job in the pool of pending jobs 206 . Because each work center 110 , 120 includes multiple machines, and because different machines at a work center may have different capabilities while generally being capable of performing the operation with which the work center is associated, each machine may be more preferable or less preferable for processing an item associated with a particular job.
- machine preference information constitutes a set of a machine preference levels reflecting the preference of each machine for processing items associated with the jobs to be processed.
- five different preference levels may exist: (1) Must—identifies machines that must be used for the current operation for reasons such as better throughput, tooling constraints, quality issues, and the like; (2) Dedicated Preferred (DP)— identifies machines that, although not mandatory, are preferred for completing the current operation; (3) Shared Preferred (SP)— identifies machines that are preferred for completing the current work order operation but not as preferable as DP machines; (4) No-Preference (NP)—identifies machines that can be used to complete the current work order operation but should only be used if no DP or SP machines are available; and (5) Must Not—identifies machines that must not be used for the current work order operation.
- these preference levels may be represented numerically, e.g.
- Machine preference levels may sometimes be referred to as “machine loading preferences” or as “machine settings”.
- An exemplary set of machine preference levels 500 for the machines of work center 110 is illustrated in FIG. 5 .
- the pool of pending jobs 206 represents the jobs in respect of which job release scheduling is to be performed. Jobs in the pool 206 generally fall into two groups.
- the first group consists of jobs for which partial release has been scheduled during the time interval preceding the time interval of interest.
- the second group consists of new jobs, i.e. jobs which have not yet been fully or partially released as of the time interval of interest. In any given run of the job release system 200 , the jobs in pool 206 may fall into either one or both of these two groups.
- the pool of pending jobs 206 is assumed to represent “lots in inventory”.
- the term “lots in inventory” refers to lots which are available in a holding location for release on the shop floor, but have not yet been released onto the shop floor.
- an optional raw material checking function allows a user of the job release system 200 to impose an additional check on the raw materials that are needed to support the production of the released lots. When this function is activated, the job release system will not release any job that has insufficient raw materials to support job processing.
- raw material inventory status 232 is retrieved from the Enterprise Database (ERP). When sufficient raw materials exist in inventory, jobs can be released to the shop floor, subject to the operative lot release constraints 202 .
- ERP Enterprise Database
- job characteristics may include an alphanumeric job identifier (e.g. A, B, C, D), a job priority (e.g. 1, 2 or 3), and a receive date (i.e. a date on which the job order was received).
- Job characteristics will include a quantity, i.e. a desired number of items to be processed.
- Other job characteristics which may be provided may include an identifier of the item(s) associated with the job and physical characteristics of the item(s) associated with the job (not illustrated).
- jobs within the pool 206 may have various forms, depending upon the production facility environment. For example, for a semiconductor assembly and test environment, a lot in inventory may constitute wafers of dies that are awaiting processing to be converted into functional packages.
- Master production schedule (MPS) 208 is an optional input defining a schedule for processing items for purposes of meeting a demand, e.g. as specified by a customer.
- MPS 208 may, for example, specify a number of semiconductor products that should be manufactured on a weekly basis for the next month to meet projected consumer demand.
- MPS 208 may alternatively be referred to as “committed customer forecast 208 ”.
- Input MPS 208 is relevant to the committed forecast job release constraint (as indicated by dashed arrow 209 ). When the committed forecast job release constraint is operative, input MPS 208 will be converted to an upper limit of a number of units to be processed per time interval for particular items, as will be described.
- some jobs in the pool of pending jobs 206 may not be identified in the MPS 208 .
- some jobs may be added to the pool of pending jobs 206 after an MPS 208 has been specified when a customer realizes with the passage of time that the MPS 208 does actually not meet the needs of emerging market conditions. Under such circumstances, any jobs that are not identified in MPS 208 will not be controlled by the committed forecast constraint.
- Pending jobs 206 and the MPS 208 may be received from an enterprise resource planning (ERP) system database 214 .
- ERP enterprise resource planning
- Job ranking criteria 210 are an optional input consisting of criteria by which new jobs (if any) within the pool of pending jobs 206 are ranked.
- Typical job ranking criteria may include job priority, customer priority, and a degree to which a job is overdue (which may be determined based on a desired shipment date and an expected processing duration, for example).
- Job priority may be an integer value representing the priority of a job (e.g. a rush job may be assigned a lower priority value indicating a higher lot priority than a non-rush job).
- Customer priority may for example be an integer value representing the priority of a customer with which a job is associated, which is usually the customer who has submitted the order.
- the degree to which a job is overdue may be expressed in terms of a critical ratio factor computed by the job release system 200 which measures the degree of “lateness” of a job based on when the job is received and a desired shipment date or loading date for the job.
- a “loading date” is a date on which it is desired for processing of the job to be initiated (“loaded” onto machines).
- WIP status 212 represents a measure of the current WIP in the production facility 100 .
- the WIP may represent a current measure of the cumulative WIP across all work centers 110 , 120 of the production facility 100 , or it may represent a current measure of the WIP at individual work centers or machines. It will be appreciated that the WIP status 212 may change from time interval to time interval as jobs are released, processed by different work centers, and completed. In the present embodiment, the WIP status 212 is determined by examination of a production database 226 associated with the production facility 100 .
- An optional input to the job release system 200 is a user-specified time interval of interest in respect of which job release scheduling is to be performed (not illustrated in FIG. 2 ). If the time interval of interest is not user-specified, it may be determined by way of a system time maintained by the job release system 200 and a predefined time interval.
- Outputs of the job release system 200 shown in FIG. 2 include a list or schedule of jobs to be released 220 during a time interval of interest and reports 222 .
- the list of jobs to be released 220 indicates which jobs from the pool of pending jobs 206 should be released during the current time interval based on job release scheduling performed by the system 200 .
- the list may for example be used to update the production database 226 with new lot release information, for such purposes as guiding a production facility supervisor as to which jobs should be processed during the next time interval.
- Reports 222 include various types of reports which may be generated by the lot release system 200 .
- one type of report may simply indicate the lot release schedule determined by the system 200 .
- Another type of report may provide an indication of machine utilization resulting from the lot release determined by the system 200 .
- a user of the job release system 200 of the present embodiment who wishes to schedule the release of jobs from the pool of pending jobs 206 for a specific time interval selects two or more job release constraints that shall be operative during operation of the system 200 .
- the job release constraints may include any two or more of (1) a baseline capacity constraint; (2) a bottleneck capacity constraint; (3) a machine preference constraint; (4) a fixture/tooling capacity constraint (if the machine preference constraint is also chosen); (5) WIP balancing constraint; (6) a committed forecast constraint; and (7) a loading pattern constraint.
- Machine information 204 Upon initiation of a job release scheduling run, machine information 204 and information about the items to be processed is obtained.
- Machine information includes information regarding the availability of the machines to be used to process the items (e.g. which machines have available time slots and when) and machine processing rate information for each of the item(s) to be processed (e.g. machine X is capable of processing Y units per hour of item I).
- machine information 204 may also include machine preference level information indicating, for each machine, the preference or suitability of that machine for processing each item. Using this information, available capacity at the machines is determined. Available machine capacity may for example be expressed as the number of units of each of the item(s) that can be processed by the machines during the time interval of interest.
- job release scheduling is performed for such jobs before it is performed for new jobs.
- the rationale for this approach is to attempt to complete jobs for which partial release has been planned in a previous time interval, in order to minimize machine setup/reconfiguration time between jobs and/or time intervals.
- the new jobs are ranked using a set of job ranking criteria. Release of new jobs is scheduled in decreasing order of determined job rank. The purpose of the ranking is to identify important or urgent jobs for which release should be scheduled first.
- Job release scheduling is performed one job at a time, with all (previously) partially released jobs (if any) being scheduled first, followed by any new jobs. Partially released jobs are scheduled for release at the same machines to which they were released in the previous time interval, in order open to minimize conversion/setup time. Accordingly, no ranking is performed for partially released jobs.
- each of the operative job release constraints is applied in order to determine the percentage of the job (e.g. the actual number of units of the item) that should be released during the current time interval. If different ones of the operative job release constraints dictate different percentages of the job which should be released, the minimum percentage meeting each of the constraints prevails.
- machine information is updated appropriately to reflect the amount of available capacity that will be consumed by the release of the prevailing percentage/number of units of the job to be released. This updated machine information will be used by the system 200 when job release scheduling is performed for the next job, so that any recently made capacity allocations will be taken into consideration during job release scheduling for the next job.
- the process is repeated either until the available machine capacity has been exhausted or until release has been scheduled for every job in the pool of pending jobs 206 .
- the job release scheduling result is generated.
- the scheduling result may for example take the form of a list of jobs which is to be used by production control personnel to dictate which jobs are to be released, and in what quantities, to the production facility 100 during the next time interval (e.g. during the next shift).
- FIGS. 6 , 7 and 9 Operation of the lot release system 200 is illustrated in FIGS. 6 , 7 and 9 , and will be described with additional reference to FIGS. 1 , 2 , 8 A, 8 B, 10 – 15 , 16 A– 16 D, and 17 .
- FIG. 6 high-level operation 600 for performing job release scheduling for a pool of pending jobs is illustrated.
- the job release system 200 ( FIG. 2 ) is initialized (S 602 ).
- Initialization entails inputting machine information 204 , inputting the operative job release constraints 202 for the current job release scheduling run, obtaining information about the pool of pending jobs 206 , and ranking any new jobs in order to determine which of the new jobs (if any) should be released first during the current time interval.
- Initialization operation S 602 is illustrated in greater detail in FIG. 7 , described below.
- Job release scheduling operation S 604 is illustrated in greater detail in FIG. 8 , described below.
- Job release results may take various forms.
- job release results may simply be updated machine allocation data and machine availability for the production facility 100 reflecting the jobs released during the time interval of interest.
- job release results may constitute or include an up-to-date lot release schedule.
- job release results may constitute or include one or more reports 222 ( FIG. 2 ) illustrating the status of the production facility 100 following job release, e.g. showing machine utilization at each of the work centers 110 and 120 of the production facility 100 . Operation 600 thus concludes.
- machine information 204 ( FIG. 2 ) is loaded into the job release system 200 (S 702 ).
- machine information 204 includes work center and routing information for the production facility 100 (e.g. which work centers including which machines are necessary to process various items, in which order), machine availability information for each machine in the production facility 100 (e.g. as shown in FIG. 3 ), machine processing rate information for each machine in the production facility 100 for various items (e.g. as shown in FIG. 4 ), and, if the machine preference job release constraint has been activated, machine preference level information representing the preference of each of the machines at production facility 100 for various items (e.g. as shown in FIG. 5 ).
- the operative job release constraints to be applied during job release scheduling are input (S 704 , FIG. 7 ).
- the operative job release constraints may be selected by a user of the job release system 200 (e.g. via a GUI associated with the system 200 ). Any two or more of the following seven constraints may be selectively activated (with some limitations as will be discussed): (1) baseline capacity constraint; (2) bottleneck capacity constraint; (3) machine preference constraint; (4) fixture/tooling capacity constraint; (5) WIP balancing constraint; (6) committed forecast constraint; and (7) loading pattern constraint. Each of these constraints is described in detail below.
- job characteristics may include such physical characteristics as package type, pad size, body size and device identifier.
- any new jobs are ranked based on user-specified set of job ranking criteria 210 (S 708 ). More than one job ranking criterion may be active at a given time.
- FIGS. 8A and 8B illustrate the manner in which multiple job ranking criteria may be applied to new jobs.
- FIGS. 8A and 8B illustrate the ranking of a set of forty new jobs.
- ranking is performed in using two sets of criteria: a primary set of ranking criteria and a secondary set of ranking criteria.
- the primary job ranking criteria are applied first in order to divide the newly received jobs into groups referred to as categories; this is shown in FIG. 8A .
- the secondary job ranking criteria are applied to each category of FIG. 8A in order to rank jobs within each category; this is shown in FIG. 8B .
- table 800 illustrates the application of four primary ranking criteria to new jobs to create five categories of jobs.
- the four primary ranking criteria that are applied in the present example are set forth in columns B to E of table 800 .
- the first primary ranking criterion (column B) is whether or not the job in question has an associated door-to-door or order-to-loading requirement.
- a door-to-door requirement is a desired duration of time between the date/time on which a job is received and the date/time on which the job is shipped.
- An order-to-loading requirement is a desired duration between the date/time on which a job is created (the “order creation date”) and the date/time on which job is released to the production facility, i.e., loaded onto machines (the “loading date”).
- the second primary ranking criterion (column C) is whether or not a job is overdue (based on critical ratio or committed shipment date).
- the third primary ranking criterion (column D) is whether or not the job priority is less than or equal to four, which is indicative of a so-called “fast track” (i.e. high priority) job in the illustrated embodiment.
- the fourth primary ranking criterion (column E) is whether or not a committed customer forecast (sometimes referred to as a “runrate commitment”) is specified for the job. That is, the fourth criterion is whether or not a job is included in a master production schedule 208 .
- each row represents a category resulting from application of the four primary criteria described above as shown in the cells of the row.
- each cell contains a value “1”, “0” or “X”. If the value in a cell is “1”, this means that a job must have the criterion represented by the column in order to be included in the category represented by the row. If the value is “0”, this means that a job must not have the criterion represented by the column in order to be included in the category represented by the row. If the value is “X” (“do not care”), the value of the criterion represented by the column does not impact upon inclusion of a job into the category represented by the row.
- the “1”, “0” and “X” values are specified by a user of the job release system 200 .
- job ranking criteria may be specified in ways other than the illustrated “1”, “0” and “X” approach, as will be recognized by those skilled in the art.
- the “1”, “0” and “X” values specified by the user in the present example result in four categories (numbered 1 to 4 ), each of which appears in a separate row of table 800 (the category number being specified in the first column A of table 800 ).
- Lower category number values are understood to indicate higher category rankings.
- jobs within highly-ranked categories will be released before jobs within less highly-ranked categories (e.g. the jobs in category 1 will all be released before any job of category 2 is released). It is implicit in table 800 that if the characteristics of a job are such that the job qualifies in more than one category, the job will only be included in the most highly-ranked qualifying category.
- the four categories of table 800 may be accordingly interpreted as follows. Jobs having an associated door-to-door or order-to-loading requirement that are overdue are ranked most highly (category 1 ), with job priority or the existence of a specified committed customer forecast for the job being immaterial to inclusion in category 1 .
- categories 1 In the next group (category 2 ) are all remaining “fast-track” jobs (except those already in category 1 ).
- a “fast-track” job is a job with a job priority of 1–4 out of a possible 10 (i.e. a high priority job).
- Ranked next in category 3
- ranked last (category 4 ) are non-fast-track jobs without a specified committed customer forecast.
- the “SD ⁇ RD” component of equation [1] represents the amount of time which has elapsed between the receipt of an incoming job order and time at which the job release system is executed. This component will have a positive value simply because an order cannot be released before it is received.
- table 810 illustrates application of three secondary ranking criteria to the five categories of jobs described above to create a unique ranking for each of the forty new jobs of the present example.
- the first column (column A) represents the resultant job ranking, which represents the order in which the job release system 200 will attempt to release the new jobs.
- the remaining three columns (columns B, C and D) represent the secondary ranking criteria to be applied in this example.
- the first secondary ranking criterion (column B) is customer priority
- the second criterion (column C) is job priority
- the third criterion (column D) is receive date.
- the secondary criteria to be applied when ranking jobs within a particular category can differ from category to category.
- the secondary job ranking criteria applied to category 1 i.e. customer priority and job priority
- the secondary job ranking criteria applied to categories 2 – 4 job priority only.
- an order of application of the criteria may be specified. For example, during ranking of jobs in category 4 , ranking is performed first based on job priority, with the receive date being used as a “tie breaker” to rank jobs of equal job priority, on a first-come first-served (FCFS) basis.
- FCFS first-come first-served
- initialization S 602 is complete.
- job release scheduling based on the operative job released constraints is performed (S 604 ). Operation S 604 is illustrated in greater detail in FIG. 9 .
- an assessment is made as to whether or not any of the jobs in the pool of pending jobs 206 were partially released during a previous time interval (S 902 ). If this assessment is made in the affirmative, another assessment is made, namely, whether it is true that available machine capacity remains and a job remains for which job release scheduling has not yet been performed (S 910 ). The purpose of the determination of S 910 is to cause job release scheduling to be terminated if the available machine capacity at the production facility 100 ( FIG. 1 ) has been exhausted or if job release scheduling has been completed for every job in the pool 206 .
- a job is selected (S 912 ). Thereafter, job release scheduling is performed for the selected job based on the current available machine capacity and upon the operative job release constraints (S 914 ). If different ones of the operative job release constraints dictate different percentages (i.e. numbers of units) of the job that should be released, the minimum percentage meeting each of the constraints will prevail. It is noted that a single job may be scheduled for released at multiple machines of a given work center during the same time interval. Thereafter, machine information 204 (e.g. machine timelines) is updated appropriately to reflect the amount of available machine capacity that will be consumed by the release of the current job (S 916 ). Operation repeats at S 910 until either the available machine capacity has been exhausted or until release has been scheduled for every partially released job.
- machine information 204 e.g. machine timelines
- the job release scheduling performed in S 914 is dependent upon which of the following seven exemplary job release constraints 202 ( FIG. 2 ) are operative.
- the baseline capacity constraint specifies a maximum number of units of any job whose characteristics match certain specified job characteristics that can be released during a single time interval.
- a baseline capacity constraint definition is a specification of one or more baseline capacity constraints.
- the job characteristics which must be present in order for a baseline capacity constraint to apply to a job are referred to as “member” characteristics.
- the rationale for specifying a baseline capacity constraint is to limit the release of jobs specifying a large quantity of units so that they will not monopolize a set of common resources (e.g. machines capable of processing many types of jobs) during a time interval. Thus, by specifying baseline capacities for several jobs, it is more likely that common production resources will be shared between various jobs during a particular time interval.
- the baseline capacity constraint definition 1000 is illustrated in FIG. 10 .
- the baseline capacity constraint definition 1000 is illustrated in the form of a table having three major rows I, II and III and three major columns A, B and C.
- Each major row represents a baseline capacity group specification, i.e., a specification of a baseline capacity constraint which is applicable to jobs matching the “member characteristics” of the group specification.
- a group specification identifier is provided in first major column A; a baseline capacity (i.e.
- major column B the maximum number of units of matching jobs that should be released during a single time interval
- major column C the “member characteristics” which must be present in a job in order for the job to match the baseline capacity group specification (and thus for the baseline capacity of column B to be applicable) are specified in major column C.
- Five member characteristics are specified in the illustrated example, each indicated in one of five minor columns into which major column C is subdivided. Specifically, the characteristics, which are particular to semiconductor products, are customer identifier, package type (e.g. package lead count), pad size, body size and device identifier; these are specified in minor columns C 1 , C 2 , C 3 , C 4 and C 5 respectively.
- major row I containing baseline capacity group specification 14SN(90X150)-13S
- the row I is subdivided into two minor rows Ia and Ib under major column C.
- Each minor row provides a distinct set of member characteristics, either one of which must be present in a job in order for the job to match the specification 14SN(90X150)-13S. Blank cells in the rows indicate that any value of the corresponding characteristic will be considered to match.
- minor row Ia specifies that, for any jobs having a package type of 16SOICN (minor column C 2 ) and a pad size of 90 ⁇ 150 (minor column C 3 ), a maximum of 150,000 units of the matching item (major column B, row I) can be released during the current time interval, regardless of the customer ID, body size and device to be processed.
- minor row Ib specifies that the same baseline capacity of 150,000 units applies to any jobs having a package type of 14SOICNM and a pad size of 93 ⁇ 140.
- major row III specifies that, for any jobs specifying a device type SMDA05C (minor column C 5 ) and a customer identifier SEM (minor column C 1 ), a maximum of 12,000 units can be released during a single time interval, regardless of the package type, pad size or body size of the device.
- FIG. 11 illustrates the job characteristics of an exemplary job “Lot 1 ” from the pool of pending jobs 206 , in the form of a table 1100 .
- Column A of table 1100 indicates the job identifier (“Job 1 ”);
- column B indicates the desired quantity of items (“13,000”);
- column C provides a customer identifier (“SEM”), and columns D–G set forth various physical characteristics of the item to be processed (a semiconductor product).
- SEM customer identifier
- the illustrated capacity constraint definition 1000 ( FIG. 10 ) is particular to the semiconductor industry.
- the member characteristics specified under column C may be different in type and in number than those specified in minor columns C 1 –C 5 of the present example.
- the bottleneck capacity constraint limits the number of items of a job that can be released during a time interval at each work center associated with a processing operation of the job to a smallest one of a maximum quantity of items capable of being processed during the time interval at any of the work centers associated with a processing operation of that job.
- the bottleneck constraint essentially restricts the released number of items of a particular job to the minimum or “weakest link” number of units of the relevant item that can be processed at any work center associated with a processing operation of the job. This minimum number of units may be a result of limitations (e.g.
- the bottleneck capacity constraint is not an absolute limit (e.g. “10,000 units max/time interval”) specified by a user, but rather is a possibly fluctuating, job-specific limit that is computed automatically by the job release system 200 based on current machine information (e.g. machine availability information and processing rate information).
- the maximum capacity for a particular work center associated with a processing operation of a specific job (expressed as a maximum number of items capable of being processed) may be computed according to equation [2]:
- the efficiency factor ⁇ (a value between 0 to 1 inclusive) represents the performance of the machine due to the condition of the machine.
- the factor ⁇ represents the ratio of the allocated available capacity to the total available capacity for a machine during the time interval. For example, if a machine is fully available during the time interval, ⁇ will be 0; if the machine has been partially allocated, ⁇ will be between 0 and 1; and if a machine has been fully allocated, ⁇ will be 1.
- the factor ⁇ is recomputed for each machine after every execution of operation S 916 ( FIG. 9 ), in order to account for any machine allocations performed during operation S 914 of FIG. 9 for previously released jobs.
- the machine preference constraint limits the number of items of a job that can be released during a time interval based on user-specified machine preference information indicating, for each machine in the production facility 100 , the preference (or suitability) of that machine for processing each job in the pool of pending jobs 206 .
- the job release scheduling performed in S 914 ( FIG. 9 ) for the currently selected job is performed in decreasing order of machine preference. This is illustrated in FIG. 12 .
- FIG. 12 illustrates a number of machine allocation chains (rows) 1200 , 1202 , 1204 and 1206 which are indicative of the preferred machines for four exemplary jobs J 1 , J 2 , J 3 and J 4 respectively.
- the chains are divided into two portions which are labelled as columns A and B.
- Column A represents preferred machines associated with work center 110 while column B represents preferred machines associated with work center 120 .
- Examining an exemplary machine allocation chain 1200 it may be seen that, when machines at work center 110 are allocated to job J 1 in S 914 ( FIG. 9 ), any available capacity on machine MC 003 is allocated first, followed by any available capacity on machines MC 004 and MC 005 , in that order.
- any available capacity on machine MC 701 is allocated first, followed by any available capacity on machines MC 702 .
- the maximum number of items of a job that can be released for a particular work center when the machine preference constraint is operative is the Qty value computed using equation [2] above.
- fixtures In order to process certain types of items, some machines require fixtures or tooling (for convenience, the term “fixture” will be assumed to include the term “tooling” hereinafter).
- the relationship between a machine and a fixture is one-to-one (i.e. a single fixture attaches to a single machine), although multiple machines may be capable of using the same fixture and multiple fixtures may be capable of being used by the same machine.
- a pool of available fixtures may be maintained for processing various types of items. Each fixture may potentially be attached to different machines, as necessary, given the items which require processing during the current time interval.
- the fixture capacity constraint indicates that, for each job, the maximum quantity of items to be released during a time interval at a work center is the maximum quantity of items capable of being processed during that time interval based on the available number of fixtures and the existence of machines having available machine capacity that are capable of using the fixtures to process the job.
- fixture capacity constraint cannot be activated unless the machine preference constraint (described above) is also activated. This is due to the fact that the utility of each fixture for processing jobs is dependent upon which specific machines are available to process jobs (since each fixture may only be compatible with certain machines). As previously indicated, of the seven job release constraints of the present embodiment, only the machine preference constraint, when activated, will result in allocation of specific machines to specific jobs.
- the fixture capacity constraint may be expressed in the context of a fixture capacity definition, which specifies one or more fixture capacity constraints.
- An exemplary fixture capacity definition is shown in FIG. 13 in the form of a table 1300 .
- Table 1300 has two rows I, II and seven columns A–G. Each row represents a fixture capacity constraint.
- Columns A–E indicate the characteristics of the item which must be present in order for a fixture capacity constraint to apply to the associated job.
- item characteristics include package lead count (column A), customer identifier (column B), pad size (column C), device (column D) and body size (column E).
- Each non-empty cell formed by an intersection of either of rows I or II with a column A–E indicates that, in order for the fixture capacity constraint represented by the containing row to apply to a job, the physical characteristic represented by the containing column for the item associated with that job) must match the value specified in the cell.
- Each empty cell indicates that, for purposes of determining whether the fixture capacity constraint represented by the containing row shall apply to a job, the value of the physical characteristic represented by the containing column for that job is immaterial.
- each fixture capacity constraint I and II is the number of fixtures in a pool of fixture available for jobs matching the characteristics specified in columns A–E (see column F) and the processing rate that can be achieved when the fixture is used (see column G). It is noted that the processing rate of column G indicates the processing rate of the machine(s) qualified to use the fixture, as the fixture itself does not have an inherent processing rate.
- FIG. 14 illustrates a fixture usage matrix 1400 that may be specified by a user to indicate, for a specific item “part_ 1 ”, which fixtures may be used to process the item and which machines those fixtures may be attached to. It will be appreciated that fixture usage matrices similar to matrix 1400 may be maintained for each item to be processed.
- each line 1404 , 1406 , 1408 , 1410 , 1412 , 1414 , 1416 and 1418 between a representation 1402 A, 1402 B, 1402 C or 1402 D of the item “part_ 1 ” and a representation of a machine group 112 or 114 see FIG.
- FIG. 14 illustrates a benefit of maintaining machine group information, namely, a reduction in the amount of data that must be maintained by the job release system 200 (since redundant information is consolidated for all machines within a machine group).
- the objective of the WIP balancing constraint is to maintain WIP accumulations at or below user-specified optimal levels across all operations of particular jobs (i.e. for “assembly lines” as a whole) and for specified work centers. Avoidance of excessive WIP accumulations is desirable because excessive WIP may increase item processing time or “cycle time” variability and may jeopardize quality control. Undesirable WIP pileups at individual work centers may result from machine down times (e.g. due to scheduled preventative maintenance, holidays, etc.).
- a user of the job release system 200 may specify both an optimum WIP level across all operations and an optimum WIP level for each dedicated operation, for different types of items to be processed.
- An optimum WIP level across operations for a particular item is a user-specified desired WIP quantity (e.g. a desired number of partially-finished units of the item) across all operations of the production facility 100 .
- An optimum WIP level for a particular item at a “dedicated operation” i.e. at a work center comprising machines that are only capable of processing that item
- the “LWIP ⁇ OWIP” term represents a degree to which WIP for all operations of the current job exceeds optimal WIP across all operations
- the “WIP i ⁇ CO i ” term represents a degree to which WIP for any dedicated operation exceeds the capacity of the work center to process the relevant items during the current time interval.
- the Qty amount is reduced by the larger of these two terms (or, if both terms are negative, the Qty amount remains the same).
- the Qty value in equation [5] may be computed using equation [2] above.
- a “dedicated operation” is an operation performed at a work center having machines which are only capable of processing the item of interest.
- the committed forecast constraint specifies a maximum number of units to be processed per time interval for jobs which are included in an MPS 208 (i.e. a “committed customer forecast” 208 ).
- the maximum number of units may be referred to as a “Daily Run Rate” or a “Daily Expected Output”.
- the target is thus an apportionment of an overall desired number of items (as expressed in MPS 208 ) over multiple time intervals.
- the committed forecast constraint specifies a target number of 10,000 units per time interval for a particular job, yet the number of items of that job is limited by another constraint (e.g. the baseline capacity constraint) to 7,000 units per time interval, job release of the lesser number of units is scheduled.
- another constraint e.g. the baseline capacity constraint
- the objective of the loading pattern constraint is to promote the highest possible degree of similarity between the characteristics of jobs released during the current time interval and the characteristics of jobs released during the immediately preceding time interval.
- the job characteristics for which similarity is sought between adjacent time intervals are physical characteristics of items to be processed.
- the rationale for the loading pattern constraint is to limit machine setup or conversion time which may result when machines which were configured for processing one item during the preceding time interval are reconfigured or set up to be capable of processing another item during the current time interval.
- Different degrees of required similarity between jobs in adjacent time intervals may be specified. Jobs whose characteristics are sufficiently similar to the characteristics of one or more jobs released for processing during the immediately preceding time interval so as to achieve a high degree of similarity are selected (S 912 of FIG. 9 ) and scheduled for job release (S 914 of FIG. 9 ) first. Then, job release scheduling is performed for jobs whose characteristics have progressively smaller degrees of similarity to the characteristics of one or more jobs released for processing during the immediately preceding time interval.
- the rationale for this approach is that higher degrees of similarity are preferable as they generally correspond to lower machine setup times. Nevertheless, some degree of similarity is better than none.
- table 1500 of FIG. 15 The specification of various levels of required similarity between characteristics of jobs in adjacent time intervals is illustrated in table 1500 of FIG. 15 .
- Each of the four rows of table 1500 specifies a different level or degree of similarity, with level 1 representing the highest degree of similarity and level 4 representing the lowest degree of similarity (levels are identified in column A).
- Columns B–F represent physical characteristics of items associated with jobs. In the present example, the items are semiconductor products, thus the characteristics are semiconductor product characteristics.
- Each cell containing a “V” represents a requirement that the physical characteristic represented by the containing column must match between jobs in adjacent time intervals in order for the degree of similarity represented by the containing row to be present.
- Each empty cell indicates that the physical characteristic represented by containing column need not match between jobs in adjacent time intervals in order for the degree of similarity represented by the containing row to be present.
- a desired degree of similarity e.g. any of levels 1 – 4 of FIG. 15
- the jobs in the preceding time interval are grouped into unique combinations or “patterns” of the relevant item characteristics for that level. Thereafter, the characteristics of each job remaining in the pool of pending jobs compared to the pattern to determine whether or not the relevant degree of similarity is present.
- FIGS. 16A , 16 B, 16 C and 16 D illustrate in tables 1600 , 1602 , 1604 and 1606 respectively the definition of characteristic “patterns” when relevant product characteristics associated with the four degrees of similarity (levels 1 – 4 ) of table 1500 are applied to an exemplary group of jobs released for processing during an immediately preceding time interval.
- the highest degree of similarity (i.e. level 1 ) is sought first between jobs in adjacent time intervals.
- the jobs in the preceding time interval are grouped into unique patterns of the requisite item characteristics, which for level 1 are customer ID, package lead count, pad size, body size, and device (columns B–F respectively of table 1500 in FIG. 15 ).
- the result is seven unique patterns I–VII, each represented by a row of table 1600 .
- the unique values for customer ID, package lead count, pad size, body size, and device are set forth in columns A–E respectively of table 1600 (column F indicates the quantity of items matching the unique to be processed during said immediately preceding time interval).
- column F indicates the quantity of items matching the unique to be processed during said immediately preceding time interval.
- the characteristics of the item (product) associated with each pending job are compared to each of the unique patterns in the rows I–V, and if they match any of the patterns, the second highest degree of similarity is present. Such jobs are scheduled for release next.
- FIG. 17 illustrates an alternative representation 1700 of the operation illustrated in FIGS. 6 , 7 and 9 .
- the illustrated “capacity provider and allocator object master” 1702 represents the portion of job release system 200 responsible for allocating available machine capacity based on multiple operative job release constraints.
- a key 1704 provides a legend to the arrows numbered “1”, “2” and “3” between the capacity provider and allocator object master 1702 and each of operation S 802 and S 804 , which arrows correspond to operations S 912 , S 914 and S 916 respectively of FIG. 9 .
- job release scheduling for such jobs may be performed after scheduling of partially released jobs is completed (S 902 of FIG. 9 ) and before the scheduling of new jobs is initiated (S 904 ).
- job releasing scheduling may be performed in accordance with operation S 910 to S 916 of FIG. 9 , in a similar manner as it is performed for new jobs or partially released jobs.
- alternative embodiments may permit only one of the job release constraints 202 to be activated at a time (with the caveat that the fixture/tooling capacity constraint can only be activated when the machine preference constraint is activated).
- the job release constraints 202 activated during a first job release scheduling run may differ from the job release constraints 202 activated during a second, subsequent job release scheduling run.
- the jobs in the pool 206 could include a further group of jobs besides the first and second groups described above (i.e. besides jobs for which partial release has been scheduled during the preceding time interval and new jobs).
- the third group of jobs comprises jobs that have been planned for release during the a time interval interest but which have yet to be physically released.
- a planner could be planning the job release for day n, but a few scheduling runs may be required before job release scheduling is finalized. In each scheduling run, some jobs may be released by the job release system. The planner could instruct the system to save the intermediate result for later retrieval by the system for further job release planning for day n.
- job release system 200 may be used to generate committed or forecast Finished Goods (FG) dates and shipment dates for pending jobs. That is, a similar mechanism as described above may be applied, but the result may not be an indication of when jobs are to be released, but rather an indication of when jobs are committed or forecast to be completed and when they are committed or forecast to be shipped.
- FG Finished Goods
- the last time interval is used as the processing start date.
- forecast FG dates and shipment dates may be determined by the system 200 based on an assessment of machine loading and forecast processing start dates.
- FIGS. 18A to 18E The manner in which the allocation process is performed during forecast FG and shipment date determination is illustrated in FIGS. 18A to 18E .
- These figures illustrate the forecast processing start dates and forecast FG dates for thirty exemplary jobs (lots) in inventory which result from the allocation of these jobs to machines over the course of three time intervals. In the example, each time interval is one day.
- table 1800 illustrates forecast processing start dates and forecast FG dates for the thirty exemplary jobs after allocation to machines as calculated on day 1 (i.e. time interval “Day 1 ”).
- the jobs are identified by lot number in a first column A, and the forecast processing start date and forecast FG dates are provided in columns B and C respectively. It is assumed that the jobs are ranked using user-selected job ranking criteria (as described above for new jobs), with job “Lot 1 ” being the most highly ranked job and job “Lot 30 ” being the least highly ranked job. It is further assumed that the processing cycle time is four days.
- the first ten jobs are designated for processing during the first time interval “Day 1 ” ( 1802 ); the next ten jobs are designated for processing during the second time interval “Day 2 ” ( 1804 ); and the last ten jobs are designated for processing during the third time interval “Day 3 ” ( 1806 ).
- the three days' “Y” capacity is used, as “Y” is reserved for newly arrived lots, which are typically urgent lots. That is, during the generation of the forecast FG and shipment dates, the system detects the presence of any job which has been previously generated with a forecast processing start date on a particular day.
- the “Y” percentage of the available capacity for Day 1 to Day 3 will be automatically reserved for newly arrived jobs during capacity allocation, leaving only the “X” percentage of capacity for the thirty jobs.
- the forecast FG date for each job is four days after its forecast processing start date.
- table 1810 illustrates forecast processing start dates and forecast FG dates for the exemplary jobs after allocation to machines as calculated for time interval “Day 2 ”.
- the first ten jobs are not shown in FIG. 18B , as it is assumed that they were released to the shop floor during time interval “Day 1 ”.
- new lots arrive, including lots A, B, C, D and E.
- the as-yet unreleased jobs (lots 11 to 30 ) and the newly arrived lots (lots A to E) are re-ranked according to the same job ranking criteria originally used to sort lots 1 to 30 , with result being a ranking of A to E and 11 to 30 , in decreasing order of rank. Allocation is performed for these twenty-five lots, with the result being indicated in FIG.
- the “Y” percentage for time interval “Day 2 ” should be fully allocated. Assuming new jobs A to E and lots 11 to 14 fully consume Day 2 's “X” percentage (as shown at 1812 ), the “Y” percentage can now be allocated to any other jobs having a forecast processing start date of Day 2 , e.g., lots 15 to 20 .
- each of lots A to E and 11 to 20 will have a forecast processing start date of Day 2 , and thus a forecast FG date of Day 6 , as illustrated in FIG. 18B .
- each of lots 19 to 30 will have a forecast processing start date of Day 3 and thus a forecast FG date of Day 7 , as illustrated in FIG. 18D .
- This process is repeated for subsequent time intervals.
- the job release system 200 may be used to assess how much machine capacity is available for order promising (Available-to-promise or ATP).
- ATP indicates how many units of a particular item or items can be processed during a time interval of interest given available capacity not committed to customer orders.
- FIG. 19 illustrates a table 1900 representing an exemplary ATP calculation for each day during a one-week time span for a part “AMD_ 14 ssop”.
- FIG. 19 is perhaps best viewed in conjunction with FIG. 20 , which illustrates a time line 2000 for the one-week span indicating some of the available-to-promise quantities set forth in FIG. 19 .
- the rows of table 1900 ( FIG. 19 ) below the first row represent ATP calculations for particular days identified in parentheses within the identifier in column A (e.g. “(D 1 )” refers to day 1 ).
- Die Inventory is an item-specific value referring to the actual quantity of dies (i.e. semiconductor dies) received and kept in inventory (e.g., see column A of FIG. 19 ). In a non-semiconductor industry example, this value may be referred to as “raw material units inventory”. This number reflects the number of items which could be manufactured based on raw materials on hand assuming infinite machine capacity. “Booked Capacity” is an item-specific value referring to the committed forecast (i.e. MPS) quantity for the relevant item for the time span in question (column C of FIG. 19 ). “Total Released Quantity” refers to the number of units released during the time span up to the beginning of the current day.
- “Balance To Go” refers to the number of units to be released on the current day and on the remaining days of the time span (column D).
- “Optimum Capacity” (OC) refers to the item-specific quantity of units that could be processed during the remaining time span given the job release constraints and machine preference settings for the relevant item (column E) which are assumed to be operational.
- “Maximum Capacity” refers to the maximum number of units of the relevant item that could be processed during the time span given the operative job release constraints and machine preference settings for the relevant item.
- spot Order per BTG refers to the size (number of units) of spot order for the relevant item that could be accommodated based on the BTG (column F).
- SOD spot Order per Die Inventory
- Optimum Capacity is an item-specific quantity
- OC could be shared by different items/products from different customers for non-dedicated (i.e. shared) work centers. For example, assume that three items from different customers (Part A, Part B, and Part C) share ten machines in work center 123 based on machine preferences specified for those items. During the computation of OC for each individual item, all the ten machine capacities are assumed to be all available for any of part A, Part B, or Part C, simultaneously. Assume availability of machine capacity for an ad hoc order for, say, part A, is being examined. If the ad hoc order consumes an equivalent of ten machines' capacity, then the OC for all three parts will be reduced to zero. Thus, although OC is considered to be an item-specific quantity, for shared operation resources, once the shared capacity is consumed by other parts, all relevant OCs will be updated accordingly.
- FIGS. 21 and 22 illustrate table 2100 and 2200 respectively in which the quantities described above in conjunction with columns B–G of FIG. 19 are illustrated (also in columns B to G) for the part AMD_ 14 ssop (as identified in column A).
- column H has a blank (zero) specified ad hoc quantity.
Abstract
Description
CR=(SD−RD+PLT)/CT [1.1]
Where:
- CR=Critical Ratio, which here is an indication of whether a job will be completed by a desired shipping date (CR>1 means that the job will be overdue)
- SD=current System Date, i.e., the date on which the job release system is being executed
- RD=Receive Date, i.e., the date on which a job is received (e.g. the date on which a work order is received at a production facility)
- PLT=Product Lead Time, i.e., the amount of time required to process a product (or, more generically, item) from initiation to completion. In a semiconductor assembly environment, product lead time is the summation of the lead times incurred in the pre-assembly, assembly and test operations.
- CT=desired “door-to-door” lead time for the job
CR=(SD−OCD)/CT [1.2]
Where:
- CR=Critical Ratio, which here is an indication of whether a job will be loaded onto machine by a date (CR>1 means that the job will be overdue)
- SD=current System Date, i.e., the date on which the job release system is being executed
- OCD=Order Creation Date
- CT=desired “order-to-loading” lead time for the job
Where:
- Qty=Number of items the work center is capable of processing
- n=Number of machines in the work center
- m=Number of items allocated to machine i during the time interval
- αi=Fractional usage factor of machine i during the time interval
- UPHij=Processing rate expressed in units per hour for machine i processing item j
- βi=Efficiency factor of machine i
- ATi=Total available time (in hours) of machine i during the time interval
BnQty=min(Qty k), kε[1,2, . . . ,N] [3]
Where:
- BnQty=Bottleneck capacity constraint for “entire assembly line” of current job
- Qtyk=Number of items work center k is capable of processing
QR=max(0,LWIP−OWIP,WIP i −CO i), iε[1,2, . . . ,N] [4]
RLQ=Qty−QR [5]
Where:
- QR=quantity to reduce
- LWIP=latest WIP between
first operation 1 and last operation N - OWIP=user-specified optimal WIP between
first operation 1 and last operation N - WIPi=latest WIP at operation i
- COi=available capacity at operation i (expressed as number of units capable of being processed during a time interval)
- N=number of dedicated operations
- RLQ=actual quantity to be released
- Qty=number of items the work center is capable of processing
CFGD=SD+PLT [6]
CSD=CFGD+SLT [7]
Where:
- CFGD=committed FG date
- SD=processing start date
- PLT=processing lead time
- CSD=committed shipment date
- SLT=shipment lead time
BTG=BC−TRQ [8]
OC=MC*LD/TD [9]
SOB=OC−BTG [10]
SOD=OC−DI [11]
Where:
- DI=die inventory
- BC=booked capacity for time span
- TRQ=total quantity released before current day
- BTG=balance to go
- OC=optimum capacity of time span
- MC=maximum capacity of time span
- LD=working days left in time span
- TD=total working days in time span
- SOB=spot order per BTG
- SOD=spot order per DI
Claims (68)
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